Sarah Stallings

Design and anticipated outcomes of the eMERGE-PGx project: a multicenter pilot for preemptive pharmacogenomics in electronic health record systems.

We describe here the design and initial implementation of the eMERGE‐PGx project. eMERGE‐PGx, a partnership of the Electronic Medical Records and Genomics Network and the Pharmacogenomics Research Network, has three objectives: (i) to deploy PGRNseq, a next‐generation sequencing platform assessing sequence variation in 84 proposed pharmacogenes, in nearly 9,000 patients likely to be prescribed drugs of interest in a 1‐ to 3‐year time frame across several clinical sites; (ii) to integrate well‐established clinically validated pharmacogenetic genotypes into the electronic health record with associated clinical decision support and to assess process and clinical outcomes of implementation; and (iii) to develop a repository of pharmacogenetic variants of unknown significance linked to a repository of electronic health record–based clinical phenotype data for ongoing pharmacogenomics discovery. We describe site‐specific project implementation and anticipated products, including genetic variant and phenotype data repositories, novel variant association studies, clinical decision support modules, clinical and process outcomes, approaches to managing incidental findings, and patient and clinician education methods.

Association of Arrhythmia-Related Genetic Variants With Phenotypes Documented in Electronic Medical Records.

IMPORTANCE Large-scale DNA sequencing identifies incidental rare variants in established Mendelian disease genes, but the frequency of related clinical phenotypes in unselected patient populations is not well established. Phenotype data from electronic medical records (EMRs) may provide a resource to assess the clinical relevance of rare variants. OBJECTIVE To determine the clinical phenotypes from EMRs for individuals with variants designated as pathogenic by expert review in arrhythmia susceptibility genes. DESIGN, SETTING, AND PARTICIPANTS This prospective cohort study included 2022 individuals recruited for nonantiarrhythmic drug exposure phenotypes from October 5, 2012, to September 30, 2013, for the Electronic Medical Records and Genomics Network Pharmacogenomics project from 7 US academic medical centers. Variants in SCN5A and KCNH2, disease genes for long QT and Brugada syndromes, were assessed for potential pathogenicity by 3 laboratories with ion channel expertise and by comparison with the ClinVar database. Relevant phenotypes were determined from EMRs, with data available from 2002 (or earlier for some sites) through September 10, 2014. EXPOSURES One or more variants designated as pathogenic in SCN5A or KCNH2. MAIN OUTCOMES AND MEASURES Arrhythmia or electrocardiographic (ECG) phenotypes defined by International Classification of Diseases, Ninth Revision (ICD-9) codes, ECG data, and manual EMR review. RESULTS Among 2022 study participants (median age, 61 years [interquartile range, 56-65 years]; 1118 [55%] female; 1491 [74%] white), a total of 122 rare (minor allele frequency <0.5%) nonsynonymous and splice-site variants in 2 arrhythmia susceptibility genes were identified in 223 individuals (11% of the study cohort). Forty-two variants in 63 participants were designated potentially pathogenic by at least 1 laboratory or ClinVar, with low concordance across laboratories (Cohen κ = 0.26). An ICD-9 code for arrhythmia was found in 11 of 63 (17%) variant carriers vs 264 of 1959 (13%) of those without variants (difference, +4%; 95% CI, -5% to +13%; P = .35). In the 1270 (63%) with ECGs, corrected QT intervals were not different in variant carriers vs those without (median, 429 vs 439 milliseconds; difference, -10 milliseconds; 95% CI, -16 to +3 milliseconds; P = .17). After manual review, 22 of 63 participants (35%) with designated variants had any ECG or arrhythmia phenotype, and only 2 had corrected QT interval longer than 500 milliseconds. CONCLUSIONS AND RELEVANCE Among laboratories experienced in genetic testing for cardiac arrhythmia disorders, there was low concordance in designating SCN5A and KCNH2 variants as pathogenic. In an unselected population, the putatively pathogenic genetic variants were not associated with an abnormal phenotype. These findings raise questions about the implications of notifying patients of incidental genetic findings.

Genetic variation among 82 pharmacogenes: The PGRNseq data from the eMERGE network

Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE‐PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of “precision medicine.” The February 2015 eMERGE‐PGx data release includes sequence‐derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation‐Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.

Genetic variation in the HLA region is associated with susceptibility to herpes zoster

Herpes zoster, commonly referred to as shingles, is caused by the varicella zoster virus (VZV). VZV initially manifests as chicken pox, most commonly in childhood, can remain asymptomatically latent in nerve tissues for many years and often re-emerges as shingles. Although reactivation may be related to immune suppression, aging and female sex, most inter-individual variability in re-emergence risk has not been explained to date. We performed a genome-wide association analyses in 22 981 participants (2280 shingles cases) from the electronic Medical Records and Genomics Network. Using Cox survival and logistic regression, we identified a genomic region in the combined and European ancestry groups that has an age of onset effect reaching genome-wide significance (P>1.0 × 10−8). This region tags the non-coding gene HCP5 (HLA Complex P5) in the major histocompatibility complex. This gene is an endogenous retrovirus and likely influences viral activity through regulatory functions. Variants in this genetic region are known to be associated with delay in development of AIDS in people infected by HIV. Our study provides further suggestion that this region may have a critical role in viral suppression and could potentially harbor a clinically actionable variant for the shingles vaccine.

Penetrance of Hemochromatosis in HFE Genotypes Resulting in p.Cys282Tyr and p.[Cys282Tyr];[His63Asp] in the eMERGE Network

Hereditary hemochromatosis (HH) is a common autosomal-recessive disorder associated with pathogenic HFE variants, most commonly those resulting in p.Cys282Tyr and p.His63Asp. Recommendations on returning incidental findings of HFE variants in individuals undergoing genome-scale sequencing should be informed by penetrance estimates of HH in unselected samples. We used the eMERGE Network, a multicenter cohort with genotype data linked to electronic medical records, to estimate the diagnostic rate and clinical penetrance of HH in 98 individuals homozygous for the variant coding for HFE p.Cys282Tyr and 397 compound heterozygotes with variants resulting in p.[His63Asp];[Cys282Tyr]. The diagnostic rate of HH in males was 24.4% for p.Cys282Tyr homozygotes and 3.5% for compound heterozygotes (p < 0.001); in females, it was 14.0% for p.Cys282Tyr homozygotes and 2.3% for compound heterozygotes (p < 0.001). Only males showed differences across genotypes in transferrin saturation levels (100% of homozygotes versus 37.5% of compound heterozygotes with transferrin saturation > 50%; p = 0.003), serum ferritin levels (77.8% versus 33.3% with serum ferritin > 300 ng/ml; p = 0.006), and diabetes (44.7% versus 28.0%; p = 0.03). No differences were found in the prevalence of heart disease, arthritis, or liver disease, except for the rate of liver biopsy (10.9% versus 1.8% [p = 0.013] in males; 9.1% versus 2% [p = 0.035] in females). Given the higher rate of HH diagnosis than in prior studies, the high penetrance of iron overload, and the frequency of at-risk genotypes, in addition to other suggested actionable adult-onset genetic conditions, opportunistic screening should be considered for p.[Cys282Tyr];[Cys282Tyr] individuals with existing genomic data.

Healthcare provider education to support integration of pharmacogenomics in practice: the eMERGE Network experience

Ten organizations within the Electronic Medical Records and Genomics Network developed programs to implement pharmacogenomic sequencing and clinical decision support into clinical settings. Recognizing the importance of informed prescribers, a variety of strategies were used to incorporate provider education to support implementation. Education experiences with pharmacogenomics are described within the context of each organizations prior involvement, including the scope and scale of implementation specific to their Electronic Medical Records and Genomics projects. We describe common and distinct education strategies, provide exemplars and share challenges. Lessons learned inform future perspectives. Future pharmacogenomics clinical implementation initiatives need to include funding toward implementing provider education and evaluating outcomes.

Concordance between Research Sequencing and Clinical Pharmacogenetic Genotyping in the eMERGE-PGx Study

There has been extensive debate about both the necessity of orthogonal confirmation of next-generation sequencing (NGS) results in Clinical Laboratory Improvement Amendments-approved laboratories and return of research NGS results to participants enrolled in research studies. In eMERGE-PGx, subjects underwent research NGS using PGRNseq and orthogonal targeted genotyping in clinical laboratories, which prompted a comparison of genotyping results between platforms. Concordance (percentage agreement) was reported for 4077 samples tested across nine combinations of research and clinical laboratories. Retesting was possible on a subset of 1792 samples, and local laboratory directors determined sources of genotype discrepancy. Research NGS and orthogonal clinical genotyping had an overall per sample concordance rate of 0.972 and per variant concordance rate of 0.997. Genotype discrepancies attributed to research NGS were because of sample switching (preanalytical errors), whereas the majority of genotype discrepancies (92.3%) attributed to clinical genotyping were because of allele dropout as a result of rare variants interfering with primer hybridization (analytical errors). These results highlight the analytical quality of clinically significant pharmacogenetic variants derived from NGS and reveal important areas for research and clinical laboratories to address with quality management programs.

Conducting a large, multi-site survey about patients' views on broad consent: challenges and solutions

BackgroundAs biobanks play an increasing role in the genomic research that will lead to precision medicine, input from diverse and large populations of patients in a variety of health care settings will be important in order to successfully carry out such studies. One important topic is participants’ views towards consent and data sharing, especially since the 2011 Advanced Notice of Proposed Rulemaking (ANPRM), and subsequently the 2015 Notice of Proposed Rulemaking (NPRM) were issued by the Department of Health and Human Services (HHS) and Office of Science and Technology Policy (OSTP). These notices required that participants consent to research uses of their de-identified tissue samples and most clinical data, and allowing such consent be obtained in a one-time, open-ended or “broad” fashion. Conducting a survey across multiple sites provides clear advantages to either a single site survey or using a large online database, and is a potentially powerful way of understanding the views of diverse populations on this topic.MethodsA workgroup of the Electronic Medical Records and Genomics (eMERGE) Network, a national consortium of 9 sites (13 separate institutions, 11 clinical centers) supported by the National Human Genome Research Institute (NHGRI) that combines DNA biorepositories with electronic medical record (EMR) systems for large-scale genetic research, conducted a survey to understand patients’ views on consent, sample and data sharing for future research, biobank governance, data protection, and return of research results.ResultsWorking across 9 sites to design and conduct a national survey presented challenges in organization, meeting human subjects guidelines at each institution, and survey development and implementation. The challenges were met through a committee structure to address each aspect of the project with representatives from all sites. Each committee’s output was integrated into the overall survey plan. A number of site-specific issues were successfully managed allowing the survey to be developed and implemented uniformly across 11 clinical centers.ConclusionsConducting a survey across a number of institutions with different cultures and practices is a methodological and logistical challenge. With a clear infrastructure, collaborative attitudes, excellent lines of communication, and the right expertise, this can be accomplished successfully.

A case study evaluating the portability of an executable computable phenotype algorithm across multiple institutions and electronic health record environments

Electronic health record (EHR) algorithms for defining patient cohorts are commonly shared as free-text descriptions that require human intervention both to interpret and implement. We developed the Phenotype Execution and Modeling Architecture (PhEMA, http://projectphema.org) to author and execute standardized computable phenotype algorithms. With PhEMA, we converted an algorithm for benign prostatic hyperplasia, developed for the electronic Medical Records and Genomics network (eMERGE), into a standards-based computable format. Eight sites (7 within eMERGE) received the computable algorithm, and 6 successfully executed it against local data warehouses and/or i2b2 instances. Blinded random chart review of cases selected by the computable algorithm shows PPV ≥90%, and 3 out of 5 sites had >90% overlap of selected cases when comparing the computable algorithm to their original eMERGE implementation. This case study demonstrates potential use of PhEMA computable representations to automate phenotyping across different EHR systems, but also highlights some ongoing challenges.